Cameras are commonly used to capture an image of a scene that includes one or more objects. Unfortunately, sometimes the images can be blurred. For example, movement of the camera and/or movement of the objects in the scene during the exposure time of the camera can cause the image to be blurred. Further, if the camera is not properly focused when the image is captured, that image will be blurred.
As digital photography becomes more and more popular, image quality assessment such as sharpness measurement has been a topic of great interest. Sharpness is generally described as the measurement of either the clarity of details or the transition of edges inside an image. Currently, there are certain methods based on measuring certain information inside the image that are used to evaluate the sharpness of an image. Unfortunately, existing methods do not accurately and consistently evaluate the level of sharpness over a broad variety of images. Additionally, it has been an especially challenging task to attain robust performance for specific image types, such as noisy images, macros, close-up portraits, night scenes, images with high contrast blurry edges and images with rich textures, etc.